Method for measuring the incidence of hospital acquired infections

ABSTRACT

Disclosed is a method and system for analyzing patient hospitalization data to determine a Nosocomial Infection Marker (NIM), the method comprising receiving from a database hospitalization data associated with at least one patient, calculating from the hospitalization data the number of specimens with non-duplicate hospital isolates (SNDHI) markers, calculating from the hospitalization data antibiotic utilization criteria (AUC) markers, and determining the nosocomial infection marker (NIM) for each patient, based upon the calculated SNDHI and AUC markers.

I. CROSS REFERENCE TO RELATED PATENT APPLICATIONS

This application is a divisional application of U.S. application Ser.No. 11/189,394 filed on Jul. 26, 2005 which claims priority to U.S.Provisional Application No. 60/591,561 filed Jul. 27, 2004 and U.S.Provisional Application No. 60/678,899 filed May 6, 2005, all of whichare herein incorporated by reference in their entireties.

II. BACKGROUND

A “hospital-acquired infection” is a localized or systemic conditionthat results from an adverse reaction to the presence of an infectiousagent(s) or its toxin(s) and that was not present or incubating at thetime of admission to the hospital. Hospital-acquired infections affectabout 2,000,000 patients per year in the U.S., causing about 90,000deaths. They are the fourth leading cause of death in the U.S., behindonly cancer, strokes, and heart disease. In addition to their humantoll, each infection costs nearly $14,000 to treat, totaling $28B eachyear in the U.S.

Consumers, employers, hospital insurers, regulatory agencies and otherswish to know how many infections occur and how many people acquire aninfection occur each year in a given hospital. However, few hospitalscan answer these questions.

The current state of the art for identifying hospital-acquiredinfections is advanced by the Centers for Disease Control and Prevention(CDC) through its National Nosocomial Infection Surveillance (NNIS)program. Under NNIS, there are 13 major site categories and 48 specificsites or types of infection for which criteria have been developed,(Garner et al., APIC Infection Control and Applied Epidemiology:Principles and Practice, 1996). The method requires specially trainedhospital clinical personnel to manually review clinical and other datafor each patient, including patient admission, transfer and dischargedata, laboratory results, pharmacy data, radiology data, physiciannotes, and nursing notes for each patient.

Here is an example of one of the forty-eight infection criteria:

DEFINITION: Other infections of the urinary tract must meet at least oneof the following criteria:

Criterion 1: Patient has organisms isolated from culture of fluid (otherthan urine) or tissue from affected site.

Criterion 2: Patient has an abscess or other evidence of infection seenon direct examination, during a surgical operation, or during ahistopathologic examination.

Criterion 3: Patient has at least two of the following signs or symptomswith no other recognized cause: fever (>38° C.), localized pain, orlocalized tenderness at the involved site and at least one of thefollowing:

a) Purulent drainage from affected site;

b) Organisms cultured from blood that are compatible with suspected siteof infection;

c) radiographic evidence of infection, e.g., abnormal ultrasound, CTscan, magnetic resonance imaging (MRI), or radiolabel scan (gallium,technetium);

d) Physician diagnosis of infection of the kidney, ureter, bladder,urethra, or tissues surrounding the retroperitoneal or perinephricspace; or

e) Physician institutes appropriate therapy for an infection of thekidney, ureter, bladder, urethra, or tissues surrounding theretroperitoneal or perinephric space.

This current state of the art for identifying hospital-acquiredinfections is a manual process that is so time consuming that nohospital has the personnel required to apply it to all patients in thehospital. Each patient admission requires at least 20 minutes todetermine if a hospital-acquired infection was present, (Gavin P J, etal., SHEA 2004). At that rate, a hospital with 20,000 yearly admissionswould require five full time trained reviewers just to measure thehospital's infection rate. Very few hospitals have this level ofstaffing for Infection Control.

In response to the lack of resources required to apply the NNIS methodto all patients within most hospitals, the NNIS program eliminated the“hospital-wide component” (the calculation of the incidence ofhospital-acquired infections throughout the hospital) in January 1999,(National Nosocomial Infections Surveillance (NNIS) System Report. Am JInfect Control 1999). As a result, most hospitals only identify certaininfections in a subset of patients at certain times of the year. Withthis limited perspective, hospitals cannot determine the full extent ofthe problem of hospital-acquired infections nor its financial impact.

Moreover, the current manual process includes many criteria that requirethe subjective judgment of hospital clinical staff. In the 20+ yearsthat the NNIS method has been used, there has been only one studyregarding its objectivity, (Emori, et al., Infect Control HospEpidemiol. 1998). That study compared the number of infections reportedfrom the same 1,136 patient charts when reviewed by three groups: NNISparticipating hospitals, CDC-trained expert reviewers and CDCepidemiologists. The number of infections found by the three groupslooking at the same 1,136 patient charts were 611, 1264 and 865,respectively. Moreover, many wish to compare the infection rates ofseveral hospitals. However, this lack of objectivity makes suchcomparisons unreliable.

III. SUMMARY

The method for identifying hospital-acquired infections that is thesubject of this patent solves the limitations of the current state ofthe art. This method is an electronic measurement of existing hospitaldata that is capable of surveying the entire hospital population. Itdoes not require the extensive manual labor of the current state of theart. Also unlike the current state of the art, it is objective andreproducible. By applying the same criteria to each patient record andhospital, different people applying this method to the same data setwould arrive at the same measurement.

This method utilizes laboratory results, pharmacy data and patientadmit-transfer-discharge data that nearly every hospital has inelectronic format. Using the described method, one is able to computethe number of Nosocomial Infection Markers (NIM). Clinical studies haveshown that the number of NIMs corresponds to the number of distincthospital-acquired infections—thereby serving as a clinically valid proxymeasure. Financial studies have demonstrated that each NIM is correlatedwith 7.5 extra days stay in the hospital and $14,000 in variabletreatment cost (risk-adjusted). Thus, the Method can also be used topredict the length of stay and cost implications of hospital-acquiredinfections.

IV. BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate several embodiments and togetherwith the description illustrate the disclosed compositions and methods:

FIG. 1 is a block diagram representing an exemplary network environmenthaving a variety of computing devices in which the present invention maybe implemented;

FIG. 2 is a block diagram representing an exemplary non-limitingcomputing device in which the present invention may be implemented; and

FIG. 3 is a block diagram representing the method of the presentinvention.

V. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Before the present methods are disclosed and described, it is to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only and is not intended to belimiting. The term “computer-readable medium” encompasses distributionmedia, intermediate storage media, execution memory of a computer, andany other medium or device capable of storing for later reading by acomputer a computer program implementing the method of this invention.Computer programs implementing the method of this invention willcommonly be distributed to users on a distribution medium such as floppydisk or CD-ROM. From there, they will often be copied to a hard disk ora similar intermediate storage medium. When the programs are to be run,they will be loaded either from their distribution medium or theirintermediate storage medium into the execution memory of the computer,configuring the computer to act in accordance with the method of thisinvention. All these operations are well-known to those skilled in theart of computer systems.

A. Definitions

As used in the specification and the appended claims, the singular forms“a,” “an” and “the” include plural referents unless the context clearlydictates otherwise. Thus, for example, reference to “an infection”includes mixtures of two or more such infections, and the like.

Ranges can be expressed herein as from “about” one particular value,and/or to “about” another particular value. When such a range isexpressed, another embodiment includes from the one particular valueand/or to the other particular value. Similarly, when values areexpressed as approximations, by use of the antecedent “about,” it willbe understood that the particular value forms another embodiment. Itwill be further understood that the endpoints of each of the ranges aresignificant both in relation to the other endpoint, and independently ofthe other endpoint. It is also understood that there are a number ofvalues disclosed herein, and that each value is also herein disclosed as“about” that particular value in addition to the value itself. Forexample, if the value “10” is disclosed, then “about 10” is alsodisclosed. It is also understood that when a value is disclosed that“less than or equal to” the value, “greater than or equal to the value”and possible ranges between values are also disclosed, as appropriatelyunderstood by the skilled artisan. For example, if the value “10” isdisclosed then “less than or equal to 10” as well as “greater than orequal to 10” is also disclosed. It is also understood that throughoutthe application, data is provided in a number of different formats, andthat this data, represents endpoints and starting points, and ranges forany combination of the data points. For example, if a particular datapoint “10” and a particular data point 15 are disclosed, it isunderstood that greater than, greater than or equal to, less than, lessthan or equal to, and equal to 10 and 15 are considered disclosed aswell as between 10 and 15.

In this specification and in the claims which follow, reference will bemade to a number of terms which shall be defined to have the followingmeanings:

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where said event or circumstance occurs and instances where itdoes not.

“Nosocomial Infection,” (NI) also known as “Hospital-acquiredInfection,” is a localized or systemic condition that results fromadverse reaction to the presence of an infectious agent(s) or itstoxin(s) and that was not present or incubating at the time of admissionto the hospital or hospital-like facility but rather was acquired duringa hospital or facility encounter.

“Nosocomial Infection Marker” (NIM) is a value associated with theoccurrence of a distinct nosocomial infection.

“Isolate” is a microorganism (bacteria, virus, fungus, yeast, parasite,protozoa) or evidence of the presence of a microorganism (e.g. DNA,serology, histology, microscopy) identified in the laboratory analysisof a specimen.

“Hospitalization” is the condition of being treated as a patient in ahospital or hospital-like facility for any length of time.

“Hospital” is any facility at which a patient can receive medicalattention.

“Class of patient” is any group of patients that are linked by a commonfeature. Such features can include, but are not limited to, diagnosis,service provider, location in hospital, physician, and age. Otherfeatures are known to those skilled in the art and are hereinspecifically contemplated.

Throughout this application, various publications are referenced. Thedisclosures of these publications in their entireties are herebyincorporated by reference into this application in order to more fullydescribe the state of the art to which this pertains. The referencesdisclosed are also individually and specifically incorporated byreference herein for the material contained in them that is discussed inthe sentence in which the reference is relied upon.

B. Exemplary Networked and Distributed Environments

One of ordinary skill in the art can appreciate that a computer or otherclient or server device can be deployed as part of a computer network,or in a distributed computing environment. In this regard, the presentinvention pertains to any computer system having any number of memory orstorage units, and any number of applications and processes occurringacross any number of storage units or volumes, which may performoperations in connection with NIM calculation. The present invention mayapply to an environment with server computers and client computersdeployed in a network environment or distributed computing environment,having remote or local storage. The present invention may also beapplied to standalone computing devices, having programming languagefunctionality, interpretation and execution capabilities for generating,receiving and transmitting information in connection with remote orlocal services.

FIG. 1 provides a schematic diagram of an exemplary networked ordistributed computing environment. The distributed computing environmentcomprises computing objects 105 a, 105 b, etc. These objects maycomprise programs, methods, data stores, programmable logic, etc. Eachobject can communicate with another object by way of the communicationsnetwork 102. This network may itself comprise other computing objectsand computing devices that provide services to the system of FIG. 1. Inaccordance with an aspect of the invention, each object 105 or device101 may contain an application that might request NIM calculationresources of a host system.

Thus, FIG. 1 illustrates an exemplary networked or distributedenvironment, with a server in communication with client computers via anetwork/bus, in which the present invention may be employed. In moredetail, a number of servers 103 a, 103 b, etc., are interconnected via acommunications network/bus 102, which may be a LAN, WAN, intranet, theInternet, etc., with a number of client or remote computing devices 101a, 101 b, 101 c, 101 d, 101 e, etc., such as a portable computer,handheld computer, thin client, networked appliance, or other device. Adatabase 104 is depicted which can reside on a server 103 a, 103 b, etc.. . . or other computing device. Database 104 can be any form of datastorage system including, but not limited to, a flat file, a relationaldatabase (SQL), and an OLAP database (MDX and/or variants thereof). Itis thus contemplated that the present invention may apply to anycomputing device in connection with which it is desirable to provideimproved NIM calculation.

C. Exemplary Computing Device

FIG. 2 and the following discussion are intended to provide a briefgeneral description of a suitable computing environment in which theinvention may be implemented. It should be understood, however, thathandheld, portable and other computing devices and computing objects ofall kinds are contemplated for use in connection with the presentinvention. While a general purpose computer is described below, this isbut one example, and the present invention may be implemented with athin client having network/bus interoperability and interaction. Thus,the present invention may be implemented in an environment of networkedhosted services in which very little or minimal client resources areimplicated, e.g., a networked environment in which the client deviceserves merely as an interface to the network/bus, such as an objectplaced in an appliance. In essence, anywhere that data may be stored orfrom which data may be retrieved is a desirable, or suitable,environment for operation of the techniques of the invention.

Although not required, the invention can be implemented via an operatingsystem, for use by a developer of services for a device or object,and/or included within application software that aids in performing NIMcalculation. Software may be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by one or more computers, such as client workstations, serversor other devices. Generally, program modules include routines, programs,objects, components, data structures and the like that performparticular tasks or implement particular abstract data types. Typically,the functionality of the program modules may be combined or distributedas desired in various embodiments. Moreover, those skilled in the artwill appreciate that the invention may be practiced with other computersystem configurations. Other well known computing systems, environments,and/or configurations that may be suitable for use with the inventioninclude, but are not limited to, personal computers (PCs), servercomputers, hand-held or laptop devices, multi-processor systems,microprocessor-based systems, programmable consumer electronics, networkPCs, minicomputers, mainframe computers and the like. The invention mayalso be practiced in distributed computing environments where tasks areperformed by remote processing devices that are linked through acommunications network/bus or other data transmission medium. In adistributed computing environment, program modules may be located inboth local and remote computer storage media including memory storagedevices and client nodes may in turn behave as server nodes.

FIG. 2 thus illustrates an example of a suitable computing systemenvironment in which the invention may be implemented, although as madeclear above, the computing system environment is only one example of asuitable computing environment and is not intended to suggest anylimitation as to the scope of use or functionality of the invention.Neither should the computing environment be interpreted as having anydependency or requirement relating to any one or combination ofcomponents illustrated in the exemplary operating environment.

With reference to FIG. 2, an exemplary system for implementing theinvention includes a general purpose computing device in the form of acomputer 101. Components of computer 101 may include, but are notlimited to, a processing unit 201, a system memory 236, and a system bus202 that couples various system components including the system memoryto the processing unit 201. The system bus 202 may be any of severaltypes of bus structures including a memory bus or memory controller, aperipheral bus, and a local bus using any of a variety of busarchitectures.

Computer 101 typically includes a variety of computer readable media.Computer readable media can be any available media that can be accessedby computer 101 and includes both volatile and nonvolatile media,removable and non-removable media. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CDROM, digital versatile disks (DVD)or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canaccessed by computer 101. Communication media typically embodiescomputer readable instructions, data structures, program modules orother data in a modulated data signal such as a carrier wave or othertransport mechanism and includes any information delivery media. Theterm “modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, and not limitation, communicationmedia includes wired media such as a wired network or direct-wiredconnection, and wireless media such as acoustic, RF, infrared and otherwireless media. Combinations of any of the above should also be includedwithin the scope of computer readable media.

The system memory 236 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 203and random access memory (RAM) 205. A basic input/output system 204(BIOS), containing the basic routines that help to transfer informationbetween elements within computer 101, such as during start-up, istypically stored in ROM 203. RAM 205 typically contains data and/orprogram modules that are immediately accessible to and/or presentlybeing operated on by processing unit 201. By way of example, and notlimitation, FIG. 2 illustrates operating system 206, applicationprograms 207, other program modules 208, and program data 209.

The computer 101 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 2 illustrates a hard disk drive 211 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 217that reads from or writes to a removable, nonvolatile magnetic disk 237,and an optical disk drive 218 that reads from or writes to a removable,nonvolatile optical disk 238, such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 211 is typically connectedto the system bus 202 through a non-removable memory interface such asinterface 210, and magnetic disk drive 217 and optical disk drive 218are typically connected to the system bus 202 by a removable memoryinterface, such as interface 216.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 2 provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 101. In FIG. 2, for example, hard disk drive 211 is illustratedas storing operating system 212, application programs 213, other programmodules 214, and program data 215. Note that these components can eitherbe the same as or different from operating system 206, applicationprograms 207, other program modules 208, and program data 209. Operatingsystem 212, application programs 213, other program modules 214, andprogram data 215 are given different numbers here to illustrate that, ata minimum, they are different copies. A user may enter commands andinformation into the computer 101 through input devices such as akeyboard 222 and pointing device 220, commonly referred to as a mouse,trackball or touch pad. Other input devices (not shown) may include amicrophone, joystick, game pad, satellite dish, scanner, or the like.These and other input devices are often connected to the processing unit201 through a user input interface 219 that is coupled to the system bus202, but may be connected by other interface and bus structures, such asa parallel port or a universal serial bus (USB). A graphics interface223 may also be connected to the system bus 202. One or more graphicsprocessing units (GPUs) 224 may communicate with graphics interface 223.A monitor 233 or other type of display device is also connected to thesystem bus 202 via an interface, such as a video interface 226, whichmay in turn communicate with video memory 225. In addition to monitor233, computers may also include other peripheral output devices such asa printer 232, which may be connected through an output peripheralinterface 231.

The computer 101 may operate in a networked or distributed environmentusing logical connections to one or more remote computers, such as aremote computer 228. The remote computer 228 may be a personal computer,a server, a router, a network PC, a peer device or other common networknode, and typically includes many or all of the elements described aboverelative to the computer 101, although only a memory storage device 229has been illustrated in FIG. 2. The logical connections depicted in FIG.2 include a local area network (LAN) 234 and a wide area network (WAN)235, but may also include other networks/buses.

When used in a LAN networking environment, the computer 101 is connectedto the LAN 234 through a network interface or adapter 227. When used ina WAN networking environment, the computer 101 typically includes amodem 221 or other means for establishing communications over the WAN235, such as the Internet. The modem 221, which may be internal orexternal, may be connected to the system bus 202 via the user inputinterface 219, or other appropriate mechanism. In a networkedenvironment, program modules depicted relative to the computer 101, orportions thereof, may be stored in the remote memory storage device. Byway of example, and not limitation, FIG. 2 illustrates remoteapplication programs 230 as residing on memory device 229. It will beappreciated that the network connections shown are exemplary and othermeans of establishing a communications link between the computers may beused.

D. Exemplary NIM Calculation Input Data

The method relies on hospitalization data collected from electronichospital information systems, including laboratory data collected fromthe laboratory information system and pharmacy ordering and dispensingdata obtained from a pharmacy information system. Hospital patientcensus or Admit-Transfer-Discharge data can be obtained from one or moreelectronic hospital information systems. This data can be stored inlight to heavy weight databases, in flat files or similar storageformats. Data can be extracted from client facilities on an ongoingbasis using a secure, HIPAA-compliant method. This non-standard data canbe cleaned and mapped into uniform data amenable to population-wideanalysis.

By way of example, and not limitation, combinations of the followingdata can be used to form hospitalization data:

1. For each patient admit, discharge and transfer (ADT):

-   -   a) Medical Record Number    -   b) Admission date    -   c) Transaction/ADT date    -   d) Transaction type/Event (A, D, T, pre-admit, etc.)    -   e) To Location (Ward)—admitted to, transferred to    -   f) From Location (Ward)—transferred from, discharged from    -   g) Site (facility) identifier, if applicable

2. For each and every microbiology and microbiology related testperformed on the patients within the hospital:

-   -   a) Facility Name/identifier    -   b) Patient Medical record number (MR#)    -   c) Encounter Date (e.g., Admission)    -   d) Patient Location when specimen collected/resulted    -   e) Source/Type of Specimen (e.g., Sputum, Blood, Urine)    -   f) Date Specimen Collected    -   g) Test Id/Name (e.g., ID & susceptibility, fungal culture,        viral panel, C. difficile toxin)    -   h) Isolate description (i.e., Microorganism name or description        of evidence of the presence of a microorganism)    -   i) Test Method (e.g. MIC, ETEST, Kirby-Bauer, EIA)    -   j) Antibiotics (if applicable, >1 antibiotic per organism        possible)    -   k) Interpreted Result (if applicable, e.g., R-esistant,        I-ntermediate, S-usceptible per antimicrobial)

3. For each patient hospitalization and antimicrobial dispensed:

-   -   a) Medical Record Number    -   b) Admission date    -   c) Antimicrobial name, dose, route administered    -   d) Date/time dispensed

E. NIM Computation

Values for the variables N, J, Y, K, X, Q, P, R, and S disclosed hereincan be selected by one of skill in the art considering such variables asthe type of facility, type of patients, type of diagnoses, type ofinfections, type of antimicrobial agents used, and other variablesrecognized by one of skill in the art.

As seen in FIG. 3, the first step in NIM computation is to compute foreach patient hospitalization the number of Specimens with Non-DuplicateHospital Isolates (SNDHI) 302 from the hospital data received 301.

An “isolate” is a microorganism (bacteria, virus, fungus, yeast,parasite, protozoa) or evidence of the presence of a microorganism (e.g.DNA, serology, histology, microscopy) identified in the laboratoryanalysis of a specimen (patient fluid or tissue submitted for laboratoryanalysis). A specimen can yield zero or more isolates.

The first step in SNDHI computation 302 is to eliminate duplicateisolates 302 a. This is done by segregating the first isolate of thesame microorganism from the same patient obtained during an N-day periodof time (N≧0), N can be selected for example, from 1-150 days or 25-50days (N can be 30 days), not limited to the present admission. For eachadditional isolate of the same microorganism from the same patientobtained within N (N≧0) days of the first isolate, if the additionalisolate is tested against one or more antimicrobial drugs and hasinterpreted antimicrobial susceptibility results that differ from thefirst isolate on fewer than J (J≧0), J can be, for example, selectedfrom 1-20 or 1-10 (J can be 3), tested drugs, the additional isolate isa duplicate. For each additional isolate of the same microorganism(based, for example, on any indicator or indicators of themicroorganism) obtained within N (N≧0) days of the first isolate, if theadditional isolate is not tested against antimicrobial drugs, theadditional isolate is a duplicate.

The second step in SNDHI computation is to eliminate isolates associatedwith specimen contamination, surveillance, and non-infected clinicalstates 302 b. By way of example, and not limitation, isolates eliminatedcan include:

-   1) Coagulase-negative staphylococci, viridans group streptococci,    and Candida species from respiratory specimens;-   2) Aspergillus species from upper respiratory specimens;-   3) Coagulase-negative Staphylococcus species, Bacillus species,    Corynebacteria species, and diptheroids isolated only from broth or    liquid laboratory culture media;-   4) Isolate results in which no microorganism species is named (e.g.    yeast, mixed flora);-   5) Isolates obtained from decubitus specimens;-   6) Isolates obtained from a specimen that yields >Y (Y>1), Y can be    selected for example, from 1-20 or 1-10 (Y can be 2), isolates;-   7) Isolates from surveillance specimens, i.e. specimens collected    when no infection at the specimen source is suspected by a    healthcare professional;-   8) Isolates from bloodstream catheter tips that are not also    obtained from blood cultures;-   9) Isolates from environmental specimens;-   10) Isolates from gynecology specimens, excluding surgical wounds;-   11) Isolates from dermatology specimens; and-   12) Urine isolates that yield fewer than 10,000 colonies/cc of    urine.

The third step in SNDHI computation is to identify hospital isolates 302c. A “hospital isolate” can be an isolate obtained from a specimencollected from a patient during or after a hospitalization. A “hospitalisolate” can be an isolate obtained from a specimen collected from apatient after being in the hospital for X consecutive days/hours, whereX>0, and hospital day 0 is the day of admission. A “hospital isolate”can also be an isolate obtained from a specimen collected from a patientwho has been a hospitalized patient one or more times within Kdays/hours prior to specimen collection, (K≧0). X can be selected, forexample, from 1-20 hours or days or 1-10 hours or days. For example, Xcan be 2. K can be selected, for example, from 1-50 or 1-20 days/hours.For example, K can be 14 days. At this point, each “hospital isolate”identified is a SNDHI and each SNDHI is given the collected date of thespecimen that yielded the hospital isolate.

In the fourth step of SNDHI computation, the sum of the computed SNDHI'scan be calculated 302 d.

The second step in NIM computation is to compute for each patienthospitalization Antibiotic Utilization Criteria (AUC) markers 303.

AUC computation comprises two steps:

Step 1. Identify episodes of antimicrobials dispensed during the courseof hospitalization 303 a.

Step 2. If the first episode of antibiotic dispensed occurred onhospital day Q>=R (R>0) and that at least one additional antibioticepisode occurred on a) each of the next S (S>0) days or b) the day ofdischarge or c) the day of death, assign one AUC marker to thehospitalization 303 b and give it the date of Q. R can be selected forexample, from 1-20 or 1-10, and S can be selected for example, from 2-20or 2-10 consecutive days. R can be hospital day 3, and S can be 3.

The final step in NIM computation 304 is to compute for each admissionthe number of NIM by one of the formulae below:

-   -   1) NIM=SNDHI    -   2) NIM=AUC

The NIM calculation formula selected can be selected by one of skill inthe art considering such variables as the type of facility, type ofpatients, types of diagnoses, type of infections, types of antimicrobialagents used, and other variables recognized by one of skill in the art.Formula selection can depend on a preliminary evaluation of SNDHI andAUC and can be conditioned such that the selection of one formula forNIM calculation can depend on the evaluation of the other formula. Forexample, the selection of formula 2, NIM=AUC, can optionally depend onthe preliminary evaluation of formula 1, NIM=SNDHI, and a certain result(e.g. 0) for formula 1. Likewise, the selection of formula 1, NIM=SNDHI,can optionally depend on the preliminary evaluation of formula 2,NIM=AUC, and a certain result (e.g. >0), and that the AUC occurredwithin P days/hours of a SNDHI.

The final NIM result can then be used for hospital quality benchmarking(ie., NIM's/total hospital admissions) and can also be used to assisthospitals developing a report of hospital-acquired infections toregulatory agencies. The final NIM result can also be used as anobjective measure upon which to compare the relative performance amongmany hospitals and to objectively measure improvements or otherwisewithin a facility over time. The NIM result can be used as a measure offinancial efficiency. The NIM result can allow hospitals to predictlength of stay and cost implications associated with hospital-acquiredinfections. The NIM result can be used to reduce the number ofhospital-acquired infections by identifying correctable processbreakdowns causing infections, and focusing hospital staff on qualityissues as they emerge.

The rate of NIMs across all admissions within a hospital divided by thenumber of admissions in that hospital over a given time period (e.g.,one year) can be compared to the same rate at other hospitals, so as toprovide an objective benchmarking measure of the hospital-wide incidenceof nosocomial infection across multiple facilities.

The profit/loss of patients with one or more NIMs can be compared to theprofit/loss of patients with no NIMs to measure the financial impact ofhospital-acquired infections. Patterns of NIMs may be used to indicate apatient care process breakdown that is likely to cause nosocomialinfections in the future.

VI. EXAMPLES

The following examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how themethods claimed herein are made and evaluated, and are intended to bepurely exemplary and are not intended to limit the disclosure. Effortshave been made to ensure accuracy with respect to numbers (e.g.,amounts, temperature, etc.), but some errors and deviations should beaccounted for. Unless indicated otherwise, parts are parts by weight,temperature is in ° C. or is at ambient temperature, and pressure is ator near atmospheric.

A. Example 1 Calculation of SNDHI

Using the following criteria: (i) as to duplicate isolates, segregatingthe first isolate of the same microorganism from the same patientobtained during an N-day period of time (where N=30) and (ii) as to“hospital isolates,” considering only those isolates obtained from aspecimen collected from a patient after being in the hospital for Xconsecutive days/hours, where X=3 days, and hospital day 0 is the day ofadmission, here are some examples of SNDHI calculation:

SNDHI Example A:

Day 0—Positive Urine—E. coli

Day 1—No Cultures

Day 2—No Cultures

Day 3—Positive Blood—MSSA

Day 4—Positive Blood—MSSA

Day 5—No Cultures

RESULT: 1 SNDHI

SNDHI Example B:

Day 0—No Cultures

Day 1—No Cultures

Day 2—No Cultures

Day 10—Positive Blood—Coag-neg Staph

Day 14—Positive Resp—Klebsiella & Pseudom

RESULT: 2 SNDHIs

SNDHI Example C:

Day 0—Positive Nasal—Influenza

Day 1—No Cultures

Day 2—No Cultures

Day 8—Positive Blood—MRSA

Day 9—Positive Respiratory—MRSA

Day 11—Positive Respiratory—Klebsiella

RESULT: 2 SNDHIs

B. Example 2 Calculation of AUC

Using the following criteria: if antimicrobials were started on or afterhospital day N, where N=3 days and were given for a) at least 4consecutive days or b) until discharge or c) death, assign one AUCmarker to the hospitalization, the following are examples of AUCcalculation:

AUC Example A:

Days 0 through 4: Azithromycin given

Day 4: Patient discharged

RESULT: 0 AUC

AUC Example B:

Days 0 through 4: Azythromycin Zithromyacin prescribed given

Day 10: Levofloxacinm given

Day 14:—Patient discharged

RESULT: 0 AUC

AUC Example C:

Days 8 through 11: Imipenum given

Day 11:—Patient dies

RESULT: 1 AUC

AUC Example D:

Days 8 through-15: Vancomycin given

Days 40 through 45: Imipenem given

Day 50—Patient discharged

RESULT: 1 AUC

C. Example 3 Calculation of NIMs

NIM Example A: (Using NIM Formula 1)

Number of SNDHIs=2

Number of AUC=0

RESULT=2 NIMs

NIM Example B: (Using NIM Formula 1)

Number of SNDHIs=3

Number of AUC=1

RESULT=3 NIMs

NIM Example C: (Using NIM Formula 2)

Number of SNDHIs=2

Number of AUC=1

RESULT=1 NIM

NIM Example D: (Using NIM Formulas 2)

Number of SNDHIs=0

Number of AUC=1

RESULT=1 NIM

NIM Example E: (Using NIM formula 1 or 2)

Number of SNDHIs=0

Number of AUC=0

RESULT=0 NIMs

D. Example 4

Evanston Northwestern Healthcare (ENH) is a three hospital,university-affiliated system comprised of two community hospitals andone tertiary-care referral hospital with more than 41,000 combinedinpatient admissions annually. Consecutive admissions to ENH for Dec. 1through 3, 2003 (n=507) and Apr. 26 through 29, 2004 (n=400) wereassessed for development of Nosocomial Infection (NI) within 30 days ofadmission by comprehensive review of electronic medical records and byNIM analysis. The two time periods were specifically selected torepresent distinct parts of the calendar year.

Nosocomial infections were defined according to published CDC criteria.An Intensive Care Unit (ICU)-associated NI was defined as an NI thatdevelops on or after the third day of an ICU stay or within 3 days ofleaving an ICU. As in the Study on the Efficacy of Nosocomial InfectionControl (SENIC), the percentage of admissions with one or more NI wasdefined as the infection percentage and the total NI to total admissionsratio ×100 was defined as the infection ratio (Haley et al., The SENICProject. Study on the efficacy of nosocomial infection control, 1980).

All medical records were available electronically. For NIM analysis, allpositive final clinical microbiology and infectious disease-associatedserology and molecular testing results were electronically collected ona daily prospective basis from the ENH laboratory information system.Additionally, the inpatient census was electronically collected everytwo hours so that patient movement through the hospital system could bedetermined.

A NIM was defined as a patient specimen with a non-duplicate hospitalisolate, where a specimen can be a collection of material obtained froma single source (e.g. blood, urine, sputum, wound). A non-duplicateisolate can be the first direct or indirect identification of amicroorganism from any specimen from the patient in the previous 30days. A non-duplicate hospital isolate can be a non-duplicate isolateobtained from a specimen collected on or after hospital day 3 or within14 days of hospital discharge (30 days for surgical wound specimens). Iftwo isolates of the same microorganism are obtained from specimenscollected within 30 days of each other and both are tested againstantimicrobial agents, then the isolate from the latter specimen can be anon-duplicate only if its interpreted susceptibility results differ onmore than two antimicrobials from the susceptibility results of thefirst isolate. Otherwise, it can be a duplicate. Results likelyassociated with specimen contamination and other non-infected clinicalstates were excluded before non-duplicate isolates were identified.

Medical records review and NIM analysis were done by separateinvestigators whose findings remained undisclosed until all possible NIwere identified. Agreement between the two methods was considereddefinitive. Therefore, a possible NI identified by both medical recordsreview and NIM analysis was considered a confirmed NI. Likewise, anadmission without a possible NI by medical records review and NIManalysis was considered negative for NI. Discrepant cases were reviewedby two infectious disease (ID) physicians whose consensus decision wasconsidered definitive. Expert chart review of discrepant possible NI hasprecedent in the evaluation of NNIS criteria, and expertepidemiologist-physician identification of NI was the reference standardto which the SENIC chart review NI identification methods were compared.Medical records review was performed by an ID physician and two medicaltechnologists with clinical microbiology research expertise. Another IDphysician provided direction and oversight and participated indiscrepancy resolution. Each study admission had 0, 1, or more NIM, and0, 1, or more NI.

Times per admission for the comprehensive review of electronic medicalrecords were recorded during the review of the first admission set. Allactivities related to this study were approved by the ENH InstitutionalReview Board.

Comprehensive medical records review identified 45 possible NI in 40admissions (infection percentage (IP)=4.4%, infection ratio (IR)=5.0).NIM analysis identified 60 possible NI in 47 admissions (IP=5.2%,IR=6.6), and 6 possible NI after the 30-day post-admission cut-off.Comparison of all possible NI identified by the two strategies yielded25 discrepancies. After discrepancy resolution, a confirmed 49 NI in 44admissions (IP=4.9%, IR=5.4) were identified. The sensitivity andspecificity of medical records review were 0.92 and 1.0, respectively.The sensitivity and specificity of NIM analysis were 0.86 and 0.984,respectively.

From 142 admissions with an ICU component, NIM analysis identified 13possible ICU-associated NI and medical records review identified 11possible ICU-associated NI. Discrepancy resolution confirmed all 11possible NI (1 bloodstream infection, 4 pneumonias, 6 urinary tractinfections) identified by medical records review (sensitivity 1.0,specificity 1.0) and 11 of 13 possible NI identified by NIM analysis(sensitivity 1.0, specificity 0.986).

Targeted prospective surveillance by hospital Infection Control, as isnow the standard practice for most U.S. hospitals, detected a total of 6NI in 6 patients during the two study periods.

NIM analysis did not detect seven confirmed NI (4 wound infections, 1pneumonia, 1 Clostridium difficile-associated diarrhea, 1 endometritis).Six of these had no corroborating microbiology data. Four of the sixwere from uncultured surgical wound infections (2 cesarean sectiondelivery wounds, 1 breast biopsy wound, and 1 post-operative abdominalwound). One additional C. difficile-associated diarrhea was not detecteddue to a laboratory information system reporting error and onebacteremia could not be resolved by expert review. Both were excludedfrom analysis. NIM analysis correctly detected four NI (1 C.difficile-associated diarrhea, 1 bloodstream infection, 1 pneumonia, 1urinary tract infection) in four admissions that were originally missedby medical records review. NIM analysis also identified 14 possible NIthat were not NI on discrepancy resolution.

The manual review of electronic medical records required an average of17 minutes per admission, or approximately 1.5 dedicated full-timeemployees per 10,000 yearly admissions. NIM analysis requiredapproximately 10 minutes of personnel time per week to maintain andquality test the ongoing data transfer mechanism, or approximately twohours per 10,000 admissions.

VII. REFERENCES

-   1. Garner J S, et al. CDC definitions for nosocomial infections. In:    Olmsted R N, ed.: APIC Infection Control and Applied Epidemiology:    Principles and Practice. St. Louis: Mosby; 1996: pp. A-1-A-20.-   2. Gavin P J, et al. Comparison of ‘Whole House’ Versus Routine    Targeted Surveillance for Detection of Nosocomial Infection. SHEA    2004.-   3. National Nosocomial Infections Surveillance (NNIS) System Report,    Data Summary from January 1990-May 1999, Issued June 1999. Am J    Infect Control 1999; 27:520-32.-   4. Emori, et al. Accuracy of reporting nosocomial infections in    intensive care unit patients to the national nosocomial infections    surveillance system: a pilot study. Infect Control Hosp Epidemiol    1998; 19:308-316.-   5. Haley R W, Quade D, Freeman H E, Bennett J V. The SENIC Project.    Study on the efficacy of nosocomial infection control (SENIC    Project). Summary of study design. Am J. Epidemiol. May 1980;    111(5):472-485.

1. A computer-readable non-transitory medium having computer-executableinstructions stored thereon for execution by a processor to perform amethod for analyzing patient hospitalization data to determine aNosocomial Infection Marker (NIM), the method comprising the steps of:receiving from a database hospitalization data associated with at leastone patient; identifying from the hospitalization data a number ofspecimens with nonduplicate hospital isolates (SNDHI) markers throughthe steps of: segregating a first isolate of a microorganism from apatient obtained during a determined first period of time; eliminatingadditional isolates of the same microorganism from the patient obtainedwithin the determined first period of time when the additional isolateswere not tested against antimicrobial drugs; eliminating each additionalisolate of the same microorganism from the patient obtained within thedetermined first period of time when the additional isolate was testedagainst antimicrobial drugs and an interpreted antimicrobialsusceptibility result of the test differs from the first isolate onfewer than a predetermined number of drugs; identifying hospitalisolates; and assigning a SNDHI marker to each hospital isolate; anddetermining the NIM for each patient, wherein the NIM is equal to thesum of the SNDHI markers for the patient.
 2. The non-transitory mediumof claim 1, wherein the step of identifying the number of SNDHI markersfurther comprises the step of eliminating isolates associated withspecimen contamination.
 3. The non-transitory medium of claim 2, whereinthe step of eliminating isolates associated with specimen contaminationcomprises eliminating isolates of any of the set of coagulase-negativestaphylococci from respiratory specimens, viridans group streptococcifrom respiratory specimens, Candida species from respiratory specimens,Aspergillus species from upper respiratory specimens, coagulase-negativeStaphylococcus species, Bacillus species, corynebacteria species,diptheroids isolated from broth or liquid laboratory culture media,isolates in which no microorganism species is named, isolates obtainedfrom decubitus specimens, and isolates obtained from species that growover a predetermined number of distinct microorganisms.
 4. Thenon-transitory medium of claim 1, wherein the patient hospitalizationdata comprises the results of laboratory analysis of specimens from thepatient.
 5. The non-transitory medium of claim 1, wherein the patienthospitalization data comprises pharmacy ordering and dispensing data. 6.The non-transitory medium of claim 1, wherein the patienthospitalization data comprises patient census data.
 7. Thenon-transitory medium of claim 1, wherein the patient hospitalizationdata comprises Admit-Transfer-Discharge data.
 8. The non-transitorymedium of claim 1, further comprising the step of displaying results ofNIM determination.
 9. The non-transitory medium of claim 1, wherein thestep of identifying the number of SNDHIs further comprises eliminatingisolates associated with surveillance.
 10. The non-transitory medium ofclaim 9, wherein the step of eliminating isolates associated withsurveillance comprises eliminating isolates from specimens collectedwhen no infection at the specimen source is suspected.
 11. Thenon-transitory medium of claim 1, wherein the step of calculating thenumber of further comprises eliminating isolates associated withnon-infected clinical states.
 12. The non-transitory medium of claim 11,wherein the step of eliminating isolates associated with non-infectedclinical states comprises eliminating any of the set of isolates frombloodstream catheter tips that are not also obtained from blood culture,environmental specimens, isolates from gynecology specimens excludingsurgical wounds, isolates from dermatology specimens, and urine isolatesthat yield fewer than 10,000 colonies/cc of urine.
 13. Thenon-transitory medium of claim 1, wherein the step of identifyinghospital isolates comprises identifying isolates obtained from specimenscollected from a patient after the patient has been in the hospital fora determined second continuous period of time.
 14. The non-transitorymedium of claim 1, wherein the step of identifying hospital isolatescomprises identifying isolates obtained from specimens collected from apatient who has been a hospitalized patient at least once within adetermined third period of time prior to specimen collection.